|
| 1 | +{ |
| 2 | + "cells": [ |
| 3 | + { |
| 4 | + "cell_type": "markdown", |
| 5 | + "id": "initial-museum", |
| 6 | + "metadata": {}, |
| 7 | + "source": [ |
| 8 | + "### `ipydatagrid` allows for an incredible level of style customisation!\n", |
| 9 | + "\n", |
| 10 | + "Styling can be applied on three layers:\n", |
| 11 | + "\n", |
| 12 | + "1. Default renderers: header (columns), corner (top left corner) and default (body)\n", |
| 13 | + "2. Overall grid style: a set of attributes that can be applied directly to the grid *without* the need for a specific renderer\n", |
| 14 | + "3. Column-specific renderers\n", |
| 15 | + "\n", |
| 16 | + "The default renderers which you can apply to the DataGrid are `default_renderer`, `header_renderer` and `corner_renderer`.\n", |
| 17 | + "\n", |
| 18 | + "The grid style property can be defined via `grid_style`. **Overall grid styles take medium priority and will override default renderer styles!** \n", |
| 19 | + "The available properties are listed below:\n", |
| 20 | + "\n", |
| 21 | + "1. `void_color`: color of the area where the grid is not painted on the canvas\n", |
| 22 | + "2. `background_color`: background color for all body cells\n", |
| 23 | + "3. `row_background_color`: row-wise background color (takes a Vega Expression)\n", |
| 24 | + "4. `column_background_color`: column-wise background color (takes a Vega Expression)\n", |
| 25 | + "5. `grid_line_color`: color of both vertical and horizontal grid lines\n", |
| 26 | + "6. `vertical_grid_line_color`: vertical grid line color\n", |
| 27 | + "7. `horizontal_grid_line_color`: horizontal grid line color\n", |
| 28 | + "8. `header_background_color`: background color for all non-body cells (index and columns)\n", |
| 29 | + "9. `header_grid_line_color`: grid line color for all non-body cells (index and columns)\n", |
| 30 | + "10. `header_vertical_grid_line_color`: vertical grid line color for all non-body cells\n", |
| 31 | + "11. `header_horizontal_grid_line_color`: horizontal grid line color for all non-body cells\n", |
| 32 | + "12. `selection_fill_color`: fill color of selected area selection_border_color : border color of selected area\n", |
| 33 | + "13. `header_selection_fill_color`: fill color of headers intersecting with selected area at column or row\n", |
| 34 | + "14. `header_selection_border_color`: border color of headers intersecting with selected area at column or row\n", |
| 35 | + "15. `cursor_fill_color`: fill color of cursor\n", |
| 36 | + "16. `cursor_border_color`: border color of cursor\n", |
| 37 | + "17. `scroll_shadow` : Dict of color parameters for scroll shadow (vertical and horizontal). Takes three paramaters:\n", |
| 38 | + " * `size` : size of shadow in pixels\n", |
| 39 | + " * `color1` : gradient color 1\n", |
| 40 | + " * `color2` : gradient color 2\n", |
| 41 | + " * `color3` : gradient color 3\n", |
| 42 | + "\n", |
| 43 | + "\n", |
| 44 | + "Column specific renderers can be specified via the `renderers` property which takes a key corresponding to the column name, and `TextRenderer` or `BarRenderer` as value. **Column-specific renderers take the highest priority and will override `grid_style` properties.**" |
| 45 | + ] |
| 46 | + }, |
| 47 | + { |
| 48 | + "cell_type": "code", |
| 49 | + "execution_count": null, |
| 50 | + "id": "applicable-groove", |
| 51 | + "metadata": {}, |
| 52 | + "outputs": [], |
| 53 | + "source": [ |
| 54 | + "import pandas as pd\n", |
| 55 | + "import numpy as np\n", |
| 56 | + "import ipydatagrid as grid\n", |
| 57 | + "\n", |
| 58 | + "np.random.seed(104)\n", |
| 59 | + "rang = 10\n", |
| 60 | + "df = pd.DataFrame(\n", |
| 61 | + " data=[np.random.randint(0, 11, rang) for i in range(rang)],\n", |
| 62 | + " index=[f\"Row {i}\" for i in range(rang)],\n", |
| 63 | + " columns=[f\"Col {i}\" for i in range(rang)],\n", |
| 64 | + ")\n", |
| 65 | + "\n", |
| 66 | + "g = grid.DataGrid(\n", |
| 67 | + " df, layout={\"height\": \"300px\", \"width\": \"800px\"}, selection_mode=\"cell\"\n", |
| 68 | + ")\n", |
| 69 | + "g" |
| 70 | + ] |
| 71 | + }, |
| 72 | + { |
| 73 | + "cell_type": "markdown", |
| 74 | + "id": "third-import", |
| 75 | + "metadata": {}, |
| 76 | + "source": [ |
| 77 | + "### Monokai-based theme for dark backgrounds\n", |
| 78 | + "Using only top-level grid styling without custom renderers" |
| 79 | + ] |
| 80 | + }, |
| 81 | + { |
| 82 | + "cell_type": "code", |
| 83 | + "execution_count": null, |
| 84 | + "id": "related-candle", |
| 85 | + "metadata": {}, |
| 86 | + "outputs": [], |
| 87 | + "source": [ |
| 88 | + "monokai = {\n", |
| 89 | + " \"background_color\": \"#2c292d\",\n", |
| 90 | + " \"grid_line_color\": \"#a698eb7a\",\n", |
| 91 | + " \"header_background_color\": \"#2c292d9a\",\n", |
| 92 | + " \"header_grid_line_color\": \"#fc98675a\",\n", |
| 93 | + " \"selection_fill_color\": \"#78dce81a\",\n", |
| 94 | + " \"selection_border_color\": \"#ffd866\",\n", |
| 95 | + " \"header_selection_fill_color\": \"#ab9df24a\",\n", |
| 96 | + " \"header_selection_border_color\": \"lawngreen\",\n", |
| 97 | + " \"cursor_fill_color\": \"#78dce87a\",\n", |
| 98 | + " \"cursor_border_color\": \"#ff6188\",\n", |
| 99 | + "}\n", |
| 100 | + "\n", |
| 101 | + "g.grid_style = monokai" |
| 102 | + ] |
| 103 | + }, |
| 104 | + { |
| 105 | + "cell_type": "markdown", |
| 106 | + "id": "satisfactory-castle", |
| 107 | + "metadata": {}, |
| 108 | + "source": [ |
| 109 | + "### Cotton candy theme for light backgrounds" |
| 110 | + ] |
| 111 | + }, |
| 112 | + { |
| 113 | + "cell_type": "code", |
| 114 | + "execution_count": null, |
| 115 | + "id": "smoking-prince", |
| 116 | + "metadata": {}, |
| 117 | + "outputs": [], |
| 118 | + "source": [ |
| 119 | + "cotton_candy = {\n", |
| 120 | + " \"background_color\": \"rgb(255, 245, 251)\",\n", |
| 121 | + " \"header_background_color\": \"rgb(207, 212, 252, 1)\",\n", |
| 122 | + " \"header_grid_line_color\": \"rgb(0, 247, 181, 0.9)\",\n", |
| 123 | + " \"vertical_grid_line_color\": \"rgb(0, 247, 181, 0.3)\",\n", |
| 124 | + " \"horizontal_grid_line_color\": \"rgb(0, 247, 181, 0.3)\",\n", |
| 125 | + " \"selection_fill_color\": \"rgb(212, 245, 255, 0.3)\",\n", |
| 126 | + " \"selection_border_color\": \"rgb(78, 174, 212)\",\n", |
| 127 | + " \"header_selection_fill_color\": \"rgb(212, 255, 239, 0.3)\",\n", |
| 128 | + " \"header_selection_border_color\": \"rgb(252, 3, 115)\",\n", |
| 129 | + " \"cursor_fill_color\": \"rgb(186, 32, 186, 0.2)\",\n", |
| 130 | + " \"cursor_border_color\": \"rgb(191, 191, 78)\",\n", |
| 131 | + "}\n", |
| 132 | + "\n", |
| 133 | + "g.grid_style = cotton_candy" |
| 134 | + ] |
| 135 | + }, |
| 136 | + { |
| 137 | + "cell_type": "markdown", |
| 138 | + "id": "cordless-delaware", |
| 139 | + "metadata": {}, |
| 140 | + "source": [ |
| 141 | + "### Watermelon themed grid\n", |
| 142 | + "\n", |
| 143 | + "Combining custom renderers and top level grid styling" |
| 144 | + ] |
| 145 | + }, |
| 146 | + { |
| 147 | + "cell_type": "code", |
| 148 | + "execution_count": null, |
| 149 | + "id": "about-worse", |
| 150 | + "metadata": {}, |
| 151 | + "outputs": [], |
| 152 | + "source": [ |
| 153 | + "watermelon = {\n", |
| 154 | + " \"column_background_color\": grid.VegaExpr(\n", |
| 155 | + " \"cell % 2 === 0 ? 'rgb(255, 130, 145, 0.5)' : 'rgb(255, 130, 145, 0.2)'\"\n", |
| 156 | + " ),\n", |
| 157 | + " \"header_vertical_grid_line_color\": \"rgb(0, 140, 86, 0.8)\",\n", |
| 158 | + " \"header_horizontal_grid_line_color\": \"rgb(0, 140, 86, 0.4)\",\n", |
| 159 | + " \"vertical_grid_line_color\": \"rgb(176, 176, 176)\",\n", |
| 160 | + " \"horizontal_grid_line_color\": \"rgb(0, 247, 181, 0)\",\n", |
| 161 | + " \"selection_fill_color\": \"rgb(235, 223, 7, 0.3)\",\n", |
| 162 | + " \"selection_border_color\": \"rgb(201, 219, 7)\",\n", |
| 163 | + " \"header_selection_fill_color\": \"rgb(235, 223, 7, 0.4)\",\n", |
| 164 | + " \"header_selection_border_color\": \"rgb(252, 3, 115)\",\n", |
| 165 | + " \"cursor_fill_color\": \"rgb(235, 7, 113, 0.4)\",\n", |
| 166 | + " \"cursor_border_color\": \"rgb(6, 191, 58, 0.9)\",\n", |
| 167 | + "}\n", |
| 168 | + "\n", |
| 169 | + "\n", |
| 170 | + "g.grid_style = watermelon\n", |
| 171 | + "g.corner_renderer = grid.TextRenderer(\n", |
| 172 | + " background_color=\"rgb(250, 242, 130)\", text_color=\"black\"\n", |
| 173 | + ")\n", |
| 174 | + "g.header_renderer = grid.TextRenderer(\n", |
| 175 | + " background_color=grid.VegaExpr(\n", |
| 176 | + " \"cell.column % 2 === 0 ? 'rgb(34, 110, 29)': 'rgb(24, 150, 19)'\"\n", |
| 177 | + " ),\n", |
| 178 | + " text_color=\"white\",\n", |
| 179 | + ")\n", |
| 180 | + "g.renderers = {\n", |
| 181 | + " \"index\": grid.TextRenderer(\n", |
| 182 | + " background_color=grid.VegaExpr(\n", |
| 183 | + " \"cell.row % 2 === 0 ? 'rgb(21, 116, 163)': 'rgb(21, 116, 163)'\"\n", |
| 184 | + " ),\n", |
| 185 | + " text_color=\"white\",\n", |
| 186 | + " )\n", |
| 187 | + "}" |
| 188 | + ] |
| 189 | + } |
| 190 | + ], |
| 191 | + "metadata": { |
| 192 | + "kernelspec": { |
| 193 | + "display_name": "Python 3", |
| 194 | + "language": "python", |
| 195 | + "name": "python3" |
| 196 | + }, |
| 197 | + "language_info": { |
| 198 | + "codemirror_mode": { |
| 199 | + "name": "ipython", |
| 200 | + "version": 3 |
| 201 | + }, |
| 202 | + "file_extension": ".py", |
| 203 | + "mimetype": "text/x-python", |
| 204 | + "name": "python", |
| 205 | + "nbconvert_exporter": "python", |
| 206 | + "pygments_lexer": "ipython3", |
| 207 | + "version": "3.9.5" |
| 208 | + } |
| 209 | + }, |
| 210 | + "nbformat": 4, |
| 211 | + "nbformat_minor": 5 |
| 212 | +} |
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